{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 简单均线策略回测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pylab import plt, mpl\n",
    "\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1990-01-02</th>\n",
       "      <td>1.2146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-03</th>\n",
       "      <td>1.2096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-04</th>\n",
       "      <td>1.2287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-05</th>\n",
       "      <td>1.2358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-08</th>\n",
       "      <td>1.2452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-09</th>\n",
       "      <td>1.1076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-10</th>\n",
       "      <td>1.0986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-11</th>\n",
       "      <td>1.0912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14</th>\n",
       "      <td>1.0940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-15</th>\n",
       "      <td>1.0949</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8330 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close\n",
       "Date              \n",
       "1990-01-02  1.2146\n",
       "1990-01-03  1.2096\n",
       "1990-01-04  1.2287\n",
       "1990-01-05  1.2358\n",
       "1990-01-08  1.2452\n",
       "...            ...\n",
       "2022-03-09  1.1076\n",
       "2022-03-10  1.0986\n",
       "2022-03-11  1.0912\n",
       "2022-03-14  1.0940\n",
       "2022-03-15  1.0949\n",
       "\n",
       "[8330 rows x 1 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = 'https://gitee.com/yanzhang2021/data/raw/master/Bloomberg/EURUSD_daily.csv'\n",
    "symbol = 'Close'\n",
    "data = pd.DataFrame(pd.read_csv(path, index_col=0,parse_dates=True).dropna()[symbol])\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of              Close\n",
       "Date              \n",
       "1990-01-02  1.2146\n",
       "1990-01-03  1.2096\n",
       "1990-01-04  1.2287\n",
       "1990-01-05  1.2358\n",
       "1990-01-08  1.2452\n",
       "...            ...\n",
       "2022-03-09  1.1076\n",
       "2022-03-10  1.0986\n",
       "2022-03-11  1.0912\n",
       "2022-03-14  1.0940\n",
       "2022-03-15  1.0949\n",
       "\n",
       "[8330 rows x 1 columns]>"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-03</th>\n",
       "      <td>1.0243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>1.0296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>1.0321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06</th>\n",
       "      <td>1.0328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07</th>\n",
       "      <td>1.0295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1565 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close\n",
       "Date              \n",
       "2000-01-03  1.0243\n",
       "2000-01-04  1.0296\n",
       "2000-01-05  1.0321\n",
       "2000-01-06  1.0328\n",
       "2000-01-07  1.0295\n",
       "...            ...\n",
       "2005-12-26  1.1845\n",
       "2005-12-27  1.1827\n",
       "2005-12-28  1.1833\n",
       "2005-12-29  1.1840\n",
       "2005-12-30  1.1849\n",
       "\n",
       "[1565 rows x 1 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data[\"2000-01-01\":\"2005-12-31\"]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# doing loops without loop code is called vectorized fashion \n",
    "n1=21*2\n",
    "n2=21*12\n",
    "\n",
    "# rolling(n)滑动窗口\n",
    "\n",
    "\n",
    "data['SMA1'] = data[symbol].rolling(n1).mean()\n",
    "data['SMA2'] = data[symbol].rolling(n2).mean()\n",
    "\n",
    "# %matplotlib widget\n",
    "data.plot(figsize=(10, 6));\n",
    "\n",
    "# data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>SMA1</th>\n",
       "      <th>SMA2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-19</th>\n",
       "      <td>0.8953</td>\n",
       "      <td>0.862126</td>\n",
       "      <td>0.923759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-20</th>\n",
       "      <td>0.9093</td>\n",
       "      <td>0.863886</td>\n",
       "      <td>0.923303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>0.9166</td>\n",
       "      <td>0.865807</td>\n",
       "      <td>0.922854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-22</th>\n",
       "      <td>0.9232</td>\n",
       "      <td>0.868093</td>\n",
       "      <td>0.922422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-25</th>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.870364</td>\n",
       "      <td>0.921997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "      <td>1.183652</td>\n",
       "      <td>1.244073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "      <td>1.183076</td>\n",
       "      <td>1.243587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "      <td>1.182698</td>\n",
       "      <td>1.243094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "      <td>1.182271</td>\n",
       "      <td>1.242591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "      <td>1.181738</td>\n",
       "      <td>1.242033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1314 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close      SMA1      SMA2\n",
       "Date                                  \n",
       "2000-12-19  0.8953  0.862126  0.923759\n",
       "2000-12-20  0.9093  0.863886  0.923303\n",
       "2000-12-21  0.9166  0.865807  0.922854\n",
       "2000-12-22  0.9232  0.868093  0.922422\n",
       "2000-12-25  0.9257  0.870364  0.921997\n",
       "...            ...       ...       ...\n",
       "2005-12-26  1.1845  1.183652  1.244073\n",
       "2005-12-27  1.1827  1.183076  1.243587\n",
       "2005-12-28  1.1833  1.182698  1.243094\n",
       "2005-12-29  1.1840  1.182271  1.242591\n",
       "2005-12-30  1.1849  1.181738  1.242033\n",
       "\n",
       "[1314 rows x 3 columns]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropna(inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>SMA1</th>\n",
       "      <th>SMA2</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-19</th>\n",
       "      <td>0.8953</td>\n",
       "      <td>0.862126</td>\n",
       "      <td>0.923759</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-20</th>\n",
       "      <td>0.9093</td>\n",
       "      <td>0.863886</td>\n",
       "      <td>0.923303</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>0.9166</td>\n",
       "      <td>0.865807</td>\n",
       "      <td>0.922854</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-22</th>\n",
       "      <td>0.9232</td>\n",
       "      <td>0.868093</td>\n",
       "      <td>0.922422</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-25</th>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.870364</td>\n",
       "      <td>0.921997</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "      <td>1.183652</td>\n",
       "      <td>1.244073</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "      <td>1.183076</td>\n",
       "      <td>1.243587</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "      <td>1.182698</td>\n",
       "      <td>1.243094</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "      <td>1.182271</td>\n",
       "      <td>1.242591</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "      <td>1.181738</td>\n",
       "      <td>1.242033</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1314 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close      SMA1      SMA2  p\n",
       "Date                                     \n",
       "2000-12-19  0.8953  0.862126  0.923759 -1\n",
       "2000-12-20  0.9093  0.863886  0.923303 -1\n",
       "2000-12-21  0.9166  0.865807  0.922854 -1\n",
       "2000-12-22  0.9232  0.868093  0.922422 -1\n",
       "2000-12-25  0.9257  0.870364  0.921997 -1\n",
       "...            ...       ...       ... ..\n",
       "2005-12-26  1.1845  1.183652  1.244073 -1\n",
       "2005-12-27  1.1827  1.183076  1.243587 -1\n",
       "2005-12-28  1.1833  1.182698  1.243094 -1\n",
       "2005-12-29  1.1840  1.182271  1.242591 -1\n",
       "2005-12-30  1.1849  1.181738  1.242033 -1\n",
       "\n",
       "[1314 rows x 4 columns]"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 创建新列p，短期均线在长期之上时，p=1 否则p=-1\n",
    "# 注意：p计算出来的依据是SMA1和SMA2，而SMA1和SMA2计算依据是当天的Close，也就是当天收盘价以后计算出的结果\n",
    "\n",
    "data['p'] = np.where(data['SMA1'] （--填空--） data['SMA2'], 1, -1)#填空data['SMA1']与data['SMA2']的大小关系\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>SMA1</th>\n",
       "      <th>SMA2</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-19</th>\n",
       "      <td>0.8953</td>\n",
       "      <td>0.862126</td>\n",
       "      <td>0.923759</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-20</th>\n",
       "      <td>0.9093</td>\n",
       "      <td>0.863886</td>\n",
       "      <td>0.923303</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>0.9166</td>\n",
       "      <td>0.865807</td>\n",
       "      <td>0.922854</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-22</th>\n",
       "      <td>0.9232</td>\n",
       "      <td>0.868093</td>\n",
       "      <td>0.922422</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-25</th>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.870364</td>\n",
       "      <td>0.921997</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "      <td>1.183652</td>\n",
       "      <td>1.244073</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "      <td>1.183076</td>\n",
       "      <td>1.243587</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "      <td>1.182698</td>\n",
       "      <td>1.243094</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "      <td>1.182271</td>\n",
       "      <td>1.242591</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "      <td>1.181738</td>\n",
       "      <td>1.242033</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1314 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close      SMA1      SMA2    p\n",
       "Date                                       \n",
       "2000-12-19  0.8953  0.862126  0.923759  NaN\n",
       "2000-12-20  0.9093  0.863886  0.923303 -1.0\n",
       "2000-12-21  0.9166  0.865807  0.922854 -1.0\n",
       "2000-12-22  0.9232  0.868093  0.922422 -1.0\n",
       "2000-12-25  0.9257  0.870364  0.921997 -1.0\n",
       "...            ...       ...       ...  ...\n",
       "2005-12-26  1.1845  1.183652  1.244073 -1.0\n",
       "2005-12-27  1.1827  1.183076  1.243587 -1.0\n",
       "2005-12-28  1.1833  1.182698  1.243094 -1.0\n",
       "2005-12-29  1.1840  1.182271  1.242591 -1.0\n",
       "2005-12-30  1.1849  1.181738  1.242033 -1.0\n",
       "\n",
       "[1314 rows x 4 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# shift(1) 将p列向下“串”一行，以求回报率;shift(-1)将某列向上串一行\n",
    "#p列同时表示“明天”做多+1还是做空-1。具体的逻辑是根据“今天”收盘价计算出来的SMA1和SMA2，如果SMA1>SMA2,上穿，则明日开始做多\n",
    "#这个判断应该是在“今日”的收盘价确定后，也就是收盘以后马上计算得出，而不能在是后盘以前得出。因为及时接近收盘，收盘价仍有可能变化\n",
    "#只有收盘后，价格才确定不变\n",
    "\n",
    "data['p'] = data['p'].shift(1)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.dropna(inplace=True)\n",
    "\n",
    "#secondary_y 表示第二个坐标轴\n",
    "data.plot(figsize=(10, 6), secondary_y='p');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>SMA1</th>\n",
       "      <th>SMA2</th>\n",
       "      <th>p</th>\n",
       "      <th>r</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-20</th>\n",
       "      <td>0.9093</td>\n",
       "      <td>0.863886</td>\n",
       "      <td>0.923303</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>0.9166</td>\n",
       "      <td>0.865807</td>\n",
       "      <td>0.922854</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.007996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-22</th>\n",
       "      <td>0.9232</td>\n",
       "      <td>0.868093</td>\n",
       "      <td>0.922422</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.007175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-25</th>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.870364</td>\n",
       "      <td>0.921997</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.002704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-26</th>\n",
       "      <td>0.9303</td>\n",
       "      <td>0.872531</td>\n",
       "      <td>0.921604</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.004957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "      <td>1.183652</td>\n",
       "      <td>1.244073</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.002024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "      <td>1.183076</td>\n",
       "      <td>1.243587</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.001521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "      <td>1.182698</td>\n",
       "      <td>1.243094</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "      <td>1.182271</td>\n",
       "      <td>1.242591</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "      <td>1.181738</td>\n",
       "      <td>1.242033</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1313 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close      SMA1      SMA2    p         r\n",
       "Date                                                 \n",
       "2000-12-20  0.9093  0.863886  0.923303 -1.0       NaN\n",
       "2000-12-21  0.9166  0.865807  0.922854 -1.0  0.007996\n",
       "2000-12-22  0.9232  0.868093  0.922422 -1.0  0.007175\n",
       "2000-12-25  0.9257  0.870364  0.921997 -1.0  0.002704\n",
       "2000-12-26  0.9303  0.872531  0.921604 -1.0  0.004957\n",
       "...            ...       ...       ...  ...       ...\n",
       "2005-12-26  1.1845  1.183652  1.244073 -1.0 -0.002024\n",
       "2005-12-27  1.1827  1.183076  1.243587 -1.0 -0.001521\n",
       "2005-12-28  1.1833  1.182698  1.243094 -1.0  0.000507\n",
       "2005-12-29  1.1840  1.182271  1.242591 -1.0  0.000591\n",
       "2005-12-30  1.1849  1.181738  1.242033 -1.0  0.000760\n",
       "\n",
       "[1313 rows x 5 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算“今日”的回报率，r=log(today's close/yesterday's close), data[symbol].shift(1)向下串一行，成为“昨日”的收盘价\n",
    "data['r'] = np.log(data[symbol] / data[symbol].shift(1))\n",
    "\n",
    "da--（填空）#填充需要输出的内容，让代码成功运行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>SMA1</th>\n",
       "      <th>SMA2</th>\n",
       "      <th>p</th>\n",
       "      <th>r</th>\n",
       "      <th>s</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>0.9166</td>\n",
       "      <td>0.865807</td>\n",
       "      <td>0.922854</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.007996</td>\n",
       "      <td>-0.007996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-22</th>\n",
       "      <td>0.9232</td>\n",
       "      <td>0.868093</td>\n",
       "      <td>0.922422</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.007175</td>\n",
       "      <td>-0.007175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-25</th>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.870364</td>\n",
       "      <td>0.921997</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.002704</td>\n",
       "      <td>-0.002704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-26</th>\n",
       "      <td>0.9303</td>\n",
       "      <td>0.872531</td>\n",
       "      <td>0.921604</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.004957</td>\n",
       "      <td>-0.004957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-12-27</th>\n",
       "      <td>0.9312</td>\n",
       "      <td>0.874676</td>\n",
       "      <td>0.921229</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000967</td>\n",
       "      <td>-0.000967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-26</th>\n",
       "      <td>1.1845</td>\n",
       "      <td>1.183652</td>\n",
       "      <td>1.244073</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.002024</td>\n",
       "      <td>0.002024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-27</th>\n",
       "      <td>1.1827</td>\n",
       "      <td>1.183076</td>\n",
       "      <td>1.243587</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.001521</td>\n",
       "      <td>0.001521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-28</th>\n",
       "      <td>1.1833</td>\n",
       "      <td>1.182698</td>\n",
       "      <td>1.243094</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000507</td>\n",
       "      <td>-0.000507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-29</th>\n",
       "      <td>1.1840</td>\n",
       "      <td>1.182271</td>\n",
       "      <td>1.242591</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000591</td>\n",
       "      <td>-0.000591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-30</th>\n",
       "      <td>1.1849</td>\n",
       "      <td>1.181738</td>\n",
       "      <td>1.242033</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.000760</td>\n",
       "      <td>-0.000760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1312 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Close      SMA1      SMA2    p         r         s\n",
       "Date                                                           \n",
       "2000-12-21  0.9166  0.865807  0.922854 -1.0  0.007996 -0.007996\n",
       "2000-12-22  0.9232  0.868093  0.922422 -1.0  0.007175 -0.007175\n",
       "2000-12-25  0.9257  0.870364  0.921997 -1.0  0.002704 -0.002704\n",
       "2000-12-26  0.9303  0.872531  0.921604 -1.0  0.004957 -0.004957\n",
       "2000-12-27  0.9312  0.874676  0.921229 -1.0  0.000967 -0.000967\n",
       "...            ...       ...       ...  ...       ...       ...\n",
       "2005-12-26  1.1845  1.183652  1.244073 -1.0 -0.002024  0.002024\n",
       "2005-12-27  1.1827  1.183076  1.243587 -1.0 -0.001521  0.001521\n",
       "2005-12-28  1.1833  1.182698  1.243094 -1.0  0.000507 -0.000507\n",
       "2005-12-29  1.1840  1.182271  1.242591 -1.0  0.000591 -0.000591\n",
       "2005-12-30  1.1849  1.181738  1.242033 -1.0  0.000760 -0.000760\n",
       "\n",
       "[1312 rows x 6 columns]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 比较可行的做法是不是这么频繁的使用dropna(),也可以让此语句只出现在最后一次编写指标之后，节省数据\n",
    "data.dropna(inplace=True)\n",
    "\n",
    "#p列表示1或者-1。1即将对应做多，-1对应做空。乘以回报率表示做多的收益率和做空的收益率，表示当日做单后的回报率\n",
    "#默认条件：开盘时以开盘价买入或者卖出，收盘时以收盘价买入或者卖出，无任何手续费以及其他成本\n",
    "data['s'] = data['p'] （--填空--） data['r']#填充计算法则字符\n",
    "\n",
    "\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "r    1.303090\n",
       "s    1.276328\n",
       "dtype: float64"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# r列表示当日市场给定的回报率，s列表示当日加入做单方向的回报率，取对数值\n",
    "data[['r', 's']].sum().apply(np.exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#取r、s两列的累积求和\n",
    "data[['r', 's']].cumsum().apply(np.exp).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#data['p'].diff() 表示p列每一个值与前一个值作差，差值不为0，则说明有均线交叉，\n",
    "# sum求总的交叉次数，+2说明第一次在数据的第一天就开始下单，无论\n",
    "#当日有没有均线交叉\n",
    "sum(data['p'].diff() != 0) + 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "#设置一个比例手续费，proportional cost，回报率-手续费比率=收入 \n",
    "pc = 0.005"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>r</th>\n",
       "      <th>s</th>\n",
       "      <th>s_</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-12-21</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.007996</td>\n",
       "      <td>-0.007996</td>\n",
       "      <td>-0.017996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-01-26</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.005000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-04-20</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.005223</td>\n",
       "      <td>-0.005223</td>\n",
       "      <td>-0.010223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-09-05</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.002704</td>\n",
       "      <td>-0.002704</td>\n",
       "      <td>-0.007704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-11-29</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.000225</td>\n",
       "      <td>0.000225</td>\n",
       "      <td>-0.004775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-05-06</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.001090</td>\n",
       "      <td>0.001090</td>\n",
       "      <td>-0.003910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-20</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.000903</td>\n",
       "      <td>0.000903</td>\n",
       "      <td>-0.004097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-24</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>-0.004593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-06-08</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.004160</td>\n",
       "      <td>0.004160</td>\n",
       "      <td>-0.000840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              p         r         s        s_\n",
       "Date                                         \n",
       "2000-12-21 -1.0  0.007996 -0.007996 -0.017996\n",
       "2001-01-26  1.0  0.000000  0.000000 -0.005000\n",
       "2001-04-20 -1.0  0.005223 -0.005223 -0.010223\n",
       "2001-09-05  1.0 -0.002704 -0.002704 -0.007704\n",
       "2001-11-29 -1.0 -0.000225  0.000225 -0.004775\n",
       "2002-05-06  1.0  0.001090  0.001090 -0.003910\n",
       "2004-09-20 -1.0 -0.000903  0.000903 -0.004097\n",
       "2004-09-24  1.0  0.000407  0.000407 -0.004593\n",
       "2005-06-08 -1.0 -0.004160  0.004160 -0.000840"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['s_'] = np.where(data['p'].diff() != 0,data['s'] - pc, data['s'])\n",
    "\n",
    "\n",
    "#回测数据第一行处进场，s_表示考量过手续费的做单回报率\n",
    "data['s_'].iloc[0] -= pc\n",
    "\n",
    "#回测数据最后一行关单收场\n",
    "data['s_'].iloc[-1] -= pc\n",
    "\n",
    "\n",
    "#对dataframe进行切片，列出所有进出场位置\n",
    "data[['p','r', 's', 's_']][data['p'].diff() != 0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "r     1.303090\n",
       "s     1.276328\n",
       "s_    1.208026\n",
       "dtype: float64"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#三列r,s,s_分别表示每天实际回报率，不考量手续费的做单回报率，以及考量手续费的做单回报率\n",
    "# apply(np.exp)的用意是，由于r已经取对数，取对数是为了计算方便，\n",
    "# 但是实际使用简单回报率更直观，所以此处使用np.exp将对数回报率转化成简单回报率\n",
    "data[['r', 's', 's_']].sum().apply(np.exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "r     0.303090\n",
       "s     0.276328\n",
       "s_    0.208026\n",
       "dtype: float64"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['r', 's', 's_']].sum().apply(np.exp) - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[['r', 's', 's_']].cumsum().apply(np.exp).plot(figsize=(10, 6));"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
